Value Addition to Insurance Data by AM Best

This white paper discusses how AM Best enhances the quality of insurance data and information. It outlines the limitations of raw, as-reported data, which can include errors, omissions, and inconsistencies that may lead to inaccurate analyses. The paper details AM Best's processes for improving data quality, including cross-checking, consolidation, and categorization of companies. It explains the importance of assigning unique identifiers to companies, which allows for consistent tracking across changes in ownership and structure. The consolidation process is described as a method to eliminate double-counting and provide a more accurate financial picture of insurance organizations. Additionally, the paper introduces the concepts of 'As-Is' and 'As-Was' analyses to present data in a way that reflects current organizational structures while also allowing for historical comparisons. Finally, it highlights the significance of categorizing companies using specific attributes to facilitate meaningful comparisons within the insurance industry.